Information presentation method and information presentation system

Abstract

This invention provides an information presentation method and system that can prevent presenting users with usage methods they cannot perform, in order to suppress battery degradation of a vehicle by encouraging them to change how they use the vehicle. [Solution] When presenting a vehicle user with a method of using the vehicle to suppress battery degradation, a method of use that is suitable for the user's vehicle usage habits is generated or selected based on usage history information regarding the user's vehicle usage history.

Description

[Technical Field]

[0001] This invention relates to an information presentation method and an information presentation system. [Background technology]

[0002] An information processing device is known that acquires status information indicating the state of a battery installed in a device, and related information indicating the relationship between the battery state and the rate of battery degradation, derives advice information indicating vehicle storage conditions to avoid battery degradation factors from the acquired status information and related information, and presents the derived advice information to the user (Patent Document 1). [Prior art documents] [Patent Documents]

[0003] [Patent Document 1] International Publication No. 2022 / 024500 [Overview of the project] [Problems that the invention aims to solve]

[0004] The conventional technology described above has a problem in that if the user is unable to change how they use the vehicle in accordance with the advice provided, it is not possible to suppress the deterioration of the vehicle's battery by prompting the user to change how they use the vehicle.

[0005] The problem that the present invention aims to solve is to provide an information presentation method and information presentation system that can prevent presenting users with usage methods they cannot perform, when the deterioration of a vehicle's battery is suppressed by encouraging users to change how they use the vehicle. [Means for solving the problem]

[0006] The present invention solves the above problem by providing a vehicle user with a method of using the vehicle to suppress battery degradation, by generating or selecting a method of use that is suitable for the user's vehicle usage habits based on usage history information regarding the user's history of using the vehicle. [Effects of the Invention]

[0007] According to the present invention, when suppressing the degradation of a vehicle's battery by prompting the user to change how the vehicle is used, it is possible to prevent presenting the user with usage methods that the user cannot perform. [Brief explanation of the drawing]

[0008] [Figure 1] This is a block diagram showing one embodiment of the information presentation system according to the present invention. [Figure 2] Figure 1 is a flowchart showing an example of the processing procedure in the information presentation system. [Figure 3] This flowchart shows another example of the processing procedure in the information presentation system shown in Figure 1. [Figure 4] This flowchart shows another example of the processing procedure in the information presentation system shown in Figure 1. [Figure 5] Another example flowchart of the processing procedure in the information presentation system shown in Figure 1. [Figure 6] Another example flowchart of the processing procedure in the information presentation system shown in Figure 1. [Modes for carrying out the invention]

[0009] Embodiments of the present invention will be described below with reference to the drawings.

[0010] [Configuration of the information presentation system] FIG. 1 is a block diagram showing an embodiment of an information presentation system according to the present invention. The information presentation system of the present embodiment is a group of devices for presenting how to use a vehicle to a user of the vehicle (hereinafter also simply referred to as a user) and prompting the user to change the way of using the vehicle. The user is not particularly limited as long as the user uses the vehicle, and in addition to the occupants of the vehicle, it also includes users of services provided via the vehicle. The vehicle of the present embodiment is a vehicle powered by a motor (or an internal combustion engine and a motor), and includes an electric vehicle (EV), a hybrid vehicle (HV), a fuel cell vehicle (FCV), and the like.

[0011] In particular, the information presentation system of the present embodiment prompts the user to change the current vehicle usage method to a specific usage method by presenting to the user a vehicle usage method (hereinafter also referred to as a specific usage method) for suppressing deterioration of the vehicle battery. The vehicle battery (hereinafter also simply referred to as a battery) is a secondary battery mounted on the vehicle, and is, for example, a lithium ion secondary battery including a all-solid-state battery. The battery supplies power to the motor that is the power source of the vehicle. The deterioration of the battery is represented by the deterioration state of the battery (hereinafter also simply referred to as the deterioration state). The deterioration state is the ratio of the current battery capacity to the initial battery capacity. The deterioration state is also referred to as the soundness or the capacity retention rate, and is also referred to as SOH (State of Health).

[0012] As shown in FIG. 1, the information presentation system 1 of the present embodiment includes a vehicle 10 and a server 20 installed outside the vehicle 10. The vehicle 10 and the server 20 are communicably connected via a telecommunication line network such as the Internet or a LAN (local area network). The communication method between the vehicle 10 and the server 20 is not particularly limited. Note that the vehicle 10 constituting the information presentation system 1 does not necessarily have to be one, and a plurality of vehicles 10 may be included in the information presentation system 1, and a plurality of vehicles 10 may be communicably connected to the server 20.

[0013] Vehicle 10 includes a vehicle control device 11, a detection device 12, and a display device 13. These devices are mounted on the vehicle 10, for example. These devices are communicably connected by known means such as wired or wireless LAN and exchange information with each other.

[0014] The vehicle control device 11 controls the devices that make up the vehicle 10 to cooperate and presents to the user how to use the vehicle. The vehicle control device 11 is, for example, a computer and includes a CPU (Central Processing Unit) as a processor, a ROM (Read Only Memory) in which programs are stored, and a RAM (Random Access Memory) that functions as an accessible storage device. The CPU of the vehicle control device 11 executes the programs stored in the ROM of the vehicle control device 11 and is an operation circuit for realizing the functions of the vehicle control device 11.

[0015] The detection device 12 detects the driving state of the vehicle 10 (hereinafter, also simply referred to as the driving state). Examples of the detection device 12 for detecting the driving state include a vehicle speed sensor, an acceleration sensor, a yaw rate sensor, and a steering angle sensor. In addition, the detection device 12 detects the state of the battery. Examples of the detection device 12 for detecting the state of the battery include a thermometer, an ammeter, and a voltmeter. As the sensor, known sensors can be used without particular limitation, and the arrangement and number thereof can be appropriately set within a range where the driving state (or the state of the battery) of the vehicle 10 can be appropriately detected. The vehicle control device 11 acquires the detection results of the detection device 12 at predetermined time intervals (for example, every 0.1 to 1 millisecond).

[0016] The display device 13 provides information to the user of the vehicle 10. The display device 13 is, for example, a liquid crystal display provided on the instrument panel, a projector such as a head-up display, and may include an input device for the user to input instructions to the vehicle control device 11 and a speaker as an output device.

[0017] Server 20 controls and coordinates the devices that make up the information presentation system 1 to set the vehicle usage method to be presented to the user. Server 20 is, for example, a computer and, like the vehicle control device 11, is equipped with a CPU, ROM, and RAM. The CPU of Server 20 is the operating circuit that executes the program stored in the ROM of Server 20 and realizes the functions of Server 20.

[0018] The ROM of server 20 stores a program for setting the vehicle usage method to be presented to the user, and the CPU of server 20 executes this program to set the vehicle usage method to be presented to the user. Figure 1 shows, for convenience, the setting unit 21, the evaluation estimation unit 22, and the preference estimation unit 23 as functional blocks for setting the vehicle usage method to be presented to the user. The functions of the vehicle control device 11, the setting unit 21, the evaluation estimation unit 22, and the preference estimation unit 23 will be described below.

[0019] [Vehicle control system and server functions] The vehicle control device 11 transmits usage history information (hereinafter also referred to as probe information or simply usage history information) regarding the history of a user's use of the vehicle 10 to the server 20 at predetermined time intervals (for example, every 0.1 to 1 millisecond). The server 20 inputs the usage history information received from the vehicle control device 11 into the setting unit 21 and / or stores it in the database 24. The database 24 stores information (for example, usage history information) organized according to certain rules. If multiple vehicles 10 are connected to the server 20 in a communicative manner, usage history information for each vehicle 10 is stored in the database 24.

[0020] The user's usage history of vehicle 10 includes the vehicle 10's driving history (hereinafter also simply referred to as driving history) and the vehicle 10's battery usage history. In other words, the usage history information includes information about the driving history and information about the battery usage history. Information about the driving history includes information about the vehicle 10's driving time, driving distance, location, driving speed, acceleration, etc. Information about the battery usage history includes information about the battery's charge level (hereinafter also simply referred to as charge level) and its changes, battery temperature, battery usage state, battery charging time, battery charging start time, and charging end time, etc. The battery usage state includes the charged state and discharge state. This information is obtained from the detection device 12. In addition, the usage history information may include at least one of the following: information about the vehicle 10's driving history, information about the battery's charging history, and information about the history of power supply from the battery to an external load of vehicle 10.

[0021] The setting unit 21 acquires usage history information from at least one of the vehicle control device 11 and the database 24, and estimates the degradation state from the usage history information at predetermined time intervals (for example, every second). The setting unit 21 may also estimate the amount of change in the degradation state over a certain period of time and calculate the amount of change in the degradation state per unit of time (i.e., the battery degradation rate). The setting unit 21 estimates the degradation state from the usage history information using, for example, at least one of a trained model that has been trained to estimate the degradation state from the usage history information (hereinafter also referred to as the first trained model) and a physical model that estimates the degradation state from information about the battery state (hereinafter also simply referred to as the physical model).

[0022] The first pre-trained model is, for example, a neural network comprising an input layer, at least one hidden layer, and an output layer. When usage history information is input to the input layer, information on the degradation state corresponding to the input usage history information is output from the output layer. The neural network is pre-trained using training data, for example, in which usage history information and information on the degradation state corresponding to the usage history information are associated. Information input to the input layer includes the charge level at the start of estimation, the battery usage period, the mileage of the vehicle 10, the amount of power consumed since the last charge was completed, the charge level at the last charge was completed, the amount of power supplied to an external load of the vehicle 10, and the ambient temperature while the vehicle 10 is parked. Information output from the output layer includes the degradation state, as well as the amount of SEI (Solid Electrolyte Interphase) formation, the temperature of the battery cells, the depth of cracks in the active material of the lithium-ion secondary battery, the concentration of the electrolyte, and the specific surface area of ​​the electrodes. SEI is a film that is mainly formed at the interface between the negative electrode and the electrolyte in a lithium-ion secondary battery, mainly during charging.

[0023] For example, if the input layer of a neural network receives information such as the current charge level, battery usage period, vehicle mileage, charge level at the end of the last charge, and ambient temperature of the battery, the hidden layer converts this information into a one-dimensional vector array. A first feature is extracted from this vector array, and the degradation state corresponding to the first feature is output to the output layer. In a neural network trained using training data, the degradation state is associated with a second feature extracted from the training data, so the degradation state corresponding to the second feature that is identical or similar to the first feature is output. The output layer outputs the information about the degradation state input from the hidden layer as an estimation result.

[0024] Whether the first feature is similar to the second feature is determined by the similarity between the first and second features (e.g., Euclidean distance). For example, if the similarity between the first and second features is greater than or equal to a predetermined similarity, the first and second features are determined to be similar; if the similarity is less than the predetermined similarity, the first and second features are determined to be dissimilar. The predetermined similarity can be set to an appropriate value within a range that allows for accurate estimation of the degradation state, for example, between 0.8 and less than 1.

[0025] The physical model is a combination of theoretical equations representing physical phenomena, such as a predictive formula for determining the amount of SEI formation, the Butler-Volmer equation for determining the battery current value, and the diffusion equation and Stefan-Maxwell equation for predicting the concentration of the electrolyte in the electrolyte solution. It estimates the degradation state from the time change of the battery state. Alternatively, the physical model may be a model that performs map calculations using a map that shows the relationship between the battery state and the degradation state. The map used in the map calculation is created in advance from information such as the results of experiments using batteries and the relationship between the battery usage history and the degradation state.

[0026] Furthermore, the setting unit 21 grasps the user's vehicle usage habits (hereinafter also referred to as "user usage habits" or simply "usage habits") from usage history information obtained from at least one of the vehicle control device 11 and the database 24. For example, the setting unit 21 grasps the timing of changes in the vehicle's driving state (or battery state) from the usage history information and extracts the user's behavioral patterns from the grasped timings. In addition, if feature quantities in a one-dimensional array vector have been set in advance for multiple usage habits, the setting unit 21 may convert the usage history information into a one-dimensional array vector, extract feature quantities from this one-dimensional array vector, and grasp the usage habits corresponding to the extracted feature quantities as the user's usage habits.

[0027] If the user's usage habits are known, the setting unit 21 identifies usage habits that affect the degradation state. Usage habits that affect the degradation state (such as usage habits that accelerate the rate of battery degradation or usage habits that accelerate the decline in the degradation state) are pre-configured and stored, for example, in the database 24. The setting unit 21 compares the known user's usage habits with the usage habits that affect the degradation state stored in the database 24 and identifies usage habits that particularly have a negative impact on the degradation state.

[0028] For example, if usage history information reveals that the battery charging starts in the evening on weekdays, is fully charged by midnight, and the vehicle 10 is moved the following morning on a regular basis (e.g., 4-5 times / week), the setting unit 21 will recognize the user's usage habit of starting battery charging after returning home on weekdays and commuting in a fully charged vehicle 10 the following morning. The setting unit 21 will also identify this usage habit as one that accelerates the battery's degradation rate. This is because, in this usage habit, the battery's charge level remains high for several hours, from the time the battery is fully charged (i.e., midnight) until the time the vehicle 10 starts moving (i.e., early morning), which puts a load on the battery.

[0029] As another example, if usage history information reveals that charging is habitually started before the battery charge level falls below 80% (for example, the time it takes for the charge level to fall below 80% is 30-60 minutes / day), the setting unit 21 recognizes the user's habit of recharging the battery when the charge level is high. The setting unit 21 also identifies this habit as one that accelerates the battery's degradation rate. This is because recharging the battery when the charge level is relatively high results in a relatively high charging voltage, which puts a load on the battery.

[0030] As another example, if usage history information reveals that the vehicle 10 is habitually parked in environments with relatively high ambient temperatures (for example, environments with temperatures of 25°C or higher) on a weekly basis (for example, 5 to 10 times a week), the setting unit 21 recognizes the user's habit of parking the vehicle 10 in relatively high ambient temperatures. The setting unit 21 also identifies this habit as one that accelerates the battery's degradation rate. This is because when the battery temperature is maintained at a relatively high temperature for a certain period of time or longer, the battery's electrolyte decreases due to active chemical reactions.

[0031] If a user's usage habit that affects the deterioration state is identified, the setting unit 21 presents the user with a specific usage method corresponding to the identified usage habit in order to encourage the user to change the identified usage habit. A specific usage method is a method of using the vehicle 10 that eliminates the factors (i.e., deterioration factors) that affect the deterioration state in a usage habit that affects the deterioration state (adversely affects the deterioration state), and one or more specific usage methods are set for a single usage habit. For example, the setting unit 21 selects a method of using the vehicle 10 that eliminates the factors that affect the deterioration state in a usage habit from a plurality of pre-set vehicle 10 usage methods and outputs it to the vehicle control device 11 as a specific usage method. A specific usage method may include a method of using the vehicle that improves at least one of the battery deterioration rate and the battery remaining lifespan.

[0032] For example, if a user has a habit of starting to charge the battery after returning home on weekdays and commuting the next morning in a fully charged vehicle 10, the setting unit 21 will present the user with at least one of the following options as a specific usage method by displaying it on the display device 13: shortening the time the vehicle 10 is left idle after charging is complete, delaying the timing of starting battery charging, and setting the maximum charge level to a certain value (e.g., 70-90%).

[0033] As another example, if a user has a habit of driving vehicle 10 500 km per day, the setting unit 21 will suggest to the user, as a specific usage method, that they reduce the daily driving distance of vehicle 10 to 200 km. If the user changes the usage method of vehicle 10 in accordance with the suggested specific usage method (i.e., the user reduces the daily driving distance of vehicle 10 to 200 km), the battery temperature will not remain high, and battery degradation will be suppressed.

[0034] However, not all users can necessarily change their usage habits of vehicle 10 to conform to the specific usage methods presented. For example, if a user's home is 200 km away from their workplace and the user uses vehicle 10 for commuting, the user cannot reduce their daily mileage to 200 km in accordance with the specific usage methods. Therefore, when the setting unit 21 presents specific usage methods to the user of vehicle 10, it generates or selects a specific usage method that is suitable for the user's usage habits based on the usage history information.

[0035] As an example, the setting unit 21 generates a specific usage method that suits the user's usage habits based on (or by combining) specific usage methods pre-registered in the database 24. As another example, the server 20 selects a specific usage method that suits the user's usage habits from among the pre-registered specific usage methods. The specific usage method generated or selected by the setting unit 21 is transmitted from the server 20 (setting unit 21) to the vehicle control device 11. The vehicle control device 11 presents the information on the specific usage method received from the server 20 to the user using a display device 13 or the like. Alternatively, the setting unit 21 may select a specific usage method that suits the user's usage habits from among a plurality of pre-configured specific usage methods based on usage history information.

[0036] For example, if a user travels daily to a location 500km away using vehicle 10, and the system suggests reducing the daily mileage of vehicle 10 to 200km as a specific usage method, the user cannot change their vehicle usage habits, and therefore battery degradation will not be suppressed. Thus, the setting unit 21 selects a specific usage method that is compatible with the user's usage habits while suppressing battery degradation, such as setting the maximum charge level to a certain value (e.g., 70-90%), and transmits this to the vehicle control device 11. The vehicle control device 11 uses the display device 13 to inform the user that the maximum charge level should be set to a certain value. Note that until the user's usage habits are understood, the vehicle control device 11 and the server 20 do not need to present specific usage methods to the user.

[0037] The setting unit 21 may generate or select a specific usage method to present to the user based on the usage history information and the degradation status. For example, if the degradation status (SOH) is relatively low and the usable time of the battery included in the usage history information is relatively short, the setting unit 21 will generate a specific usage method that shortens the driving distance of the vehicle 10.

[0038] The evaluation estimation unit 22 estimates the user's evaluation of a specific usage method based on information related to that specific usage method and usage history information acquired after the specific usage method is presented, when the vehicle control device 11 presents a specific usage method to the user. For example, if the usage history information acquired after the specific usage method is presented detects a state that is the same as the state of the vehicle defined in the specific usage method, the evaluation estimation unit 22 estimates that the user's evaluation of the presented specific usage method is higher than if the usage history information acquired after the specific usage method is presented detects a state that is different from the state of the vehicle defined in the specific usage method.

[0039] The preference estimation unit 23 estimates a preference level (hereinafter also simply referred to as "preference level") for each user, based on the evaluation estimated by the evaluation estimation unit 22, indicating the degree to which the user prefers a particular method of use. The preference level corresponds to the likelihood that the user will change their vehicle usage habits in accordance with the presented specific method of use, and indicates the degree to which the presented specific method of use is suitable for the user's usage habits. In other words, if a specific method of use with a high user preference level is presented, the user is more likely to change their usage habits than if a specific method of use with a low user preference level were presented. For example, if the evaluation estimated by the evaluation estimation unit 22 is high, the preference estimation unit 23 estimates that the user's preference for the specific method of use is higher than if the evaluation estimated by the evaluation estimation unit 22 is low.

[0040] The setting unit 21 sets the priority for presenting specific usage methods to the user based on the preference level estimated by the preference estimation unit 23. Priority is the order in which specific usage methods are presented to the user when there are multiple candidates for specific usage methods (i.e., the order of specific usage methods). The setting unit 21 sets a higher priority (order of specific usage methods) for specific usage methods the higher the preference level estimated by the preference estimation unit 23.

[0041] Furthermore, if a priority has already been set for presenting specific usage methods to the user, the setting unit 21 may update the priority based on preference. For example, if a preference is newly estimated for a second specific usage method that was previously estimated to have a lower preference than the first specific usage method, and the preference for the second specific usage method becomes higher than that of the first specific usage method, the setting unit 21 updates the priority and sets the priority of the second specific usage method higher than that of the first specific usage method.

[0042] The setting unit 21 may estimate the battery degradation state at at least two different points in time from the usage history information and calculate the battery degradation rate from the two estimated degradation states. The setting unit 21 may also generate or select a specific usage method to present to the user based on at least one of the calculated degradation rate and the usage history information. For example, if the calculated degradation rate is relatively fast, the setting unit 21 may generate or select a specific usage method to suppress the increase in the degradation rate.

[0043] The evaluation estimation unit 22 may calculate a first statistical value representing the characteristics of the usage history information from the usage history information after presenting a specific usage method to the user, calculate a second statistical value representing the characteristics of the usage history information calculated from the usage history information when the vehicle 10 is used in accordance with the specific usage method presented to the user, and calculate the similarity between the first statistical value and the second statistical value. The first and second statistical values ​​are, for example, feature quantities extracted from a one-dimensional array vector. The similarity is not particularly limited and may be cosine similarity, or the similarity may be calculated based on Euclidean distance, Manhattan distance, Hamming distance, etc.

[0044] Furthermore, the evaluation estimation unit 22 may calculate a user's evaluation of a specific usage method based on the calculated similarity. That is, if the similarity is equal to or greater than a predetermined similarity, it is determined that the user's evaluation of the specific usage method presented to the user is high, and if the similarity is less than the predetermined similarity, it is determined that the user's evaluation of the specific usage method presented to the user is low. Note that the user's evaluation may be continuous or discrete.

[0045] For example, suppose a specific usage method is presented to the user to shorten the waiting time after charging is complete. In this case, regarding the change in the charge rate before and after the battery is fully charged, a first statistical value v1 shown by the following formula (1) is calculated from the usage history information after the specific usage method is presented to the user, and a second statistical value v2 shown by the following formula (2) is calculated from the usage history information when the vehicle 10 is used in accordance with the specific usage method presented to the user.

[0046] v1 = (actual charging rate at the end of charging, actual elapsed time of the battery after charging, actual outside air temperature) T ···(1) v2 = (recommended charging rate at the end of charging, allowable elapsed time of the battery after charging, recommended outside air temperature) T ···(2)

[0047] In this case, the cosine similarity S(v1, v2) between the first statistical value v1 and the second statistical value v2 is calculated by the following formula (3).

[0048]

Equation

[0049] For example, when the value of the cosine similarity S(v1, v2) is 0.5 or more, it is estimated that the first statistical value v1 and the second statistical value v2 are the same or similar, and it is estimated that the user has accepted the presented specific usage method, and the evaluation of the user for the presented specific usage method is calculated highly. On the other hand, when the value of the cosine similarity S(v1, v2) is less than 0.5, it is estimated that the first statistical value v1 and the second statistical value v2 are dissimilar, and it is estimated that the user has rejected the presented specific usage method, and the evaluation of the user for the presented specific usage method is calculated low. Note that the cosine similarity S(v1, v2) takes a value in the interval [-1, 1].

[0050] The preference estimation unit 23 may calculate the preference for a plurality of usage methods in an encoded vector form. For example, for a specific usage method d i the whole of which is the set D = {d1, d2, d3 ··· d M}, and for the user u i the whole of which is the set U = {u1, u2, u3 ··· u N}, and if the preference of the user u i for the specific usage method d i is p i,j (however, 0 ≤ p i,j ≤ 1), then the preference of the user u i for the whole of the specific usage methods is the vector p j = (p 1,j , p 2,j , p3,j ···p M,j ) T ∈[0,1] M It is expressed as follows.

[0051] The preference estimation unit 23 may estimate the preference for multiple usage methods from the user's evaluation using at least one of a pre-set rule and a trained model (hereinafter also referred to as the second trained model) that has been machine-learned to output the preference for a specific usage method when a user evaluation is input. For example, if the user's evaluation is expressed in three stages: "low," "medium," and "high," and a rule is pre-set to classify the preference for a specific usage method that the user evaluates as "low" or "medium" as "low," and the preference for a specific usage method that the user evaluates as "high" as "high," then the preference estimation unit 23 will estimate the preference for the specific usage method as "low" or "high" in accordance with the pre-set rule.

[0052] The second pre-trained model is, for example, a neural network comprising an input layer, at least one hidden layer, and an output layer. When information about a user's evaluation is input to the input layer, preference information corresponding to the input evaluation is output from the output layer. The neural network is pre-trained using, for example, training data in which information about user evaluations and preference information are associated.

[0053] If the evaluation estimation unit 22 calculates a user's evaluation, the preference estimation unit 23 may update the user's preference based on the user's evaluation calculated immediately before and evaluations calculated before the immediately preceding evaluation. For example, the preference estimation unit 23 calculates a new user preference by adding the existing user preference and the user's latest evaluation of a specific usage method. Alternatively, the preference estimation unit 23 may store the user and their preference in the database 24, associating them for each user.

[0054] The setting unit 21 may determine whether or not there is a specific usage method in which the user's preference level is above a predetermined preference level. If it is determined that there is no specific usage method in which the user's preference level is above a predetermined preference level, the setting unit 21 does not set a specific usage method, and no specific usage method is presented to the user. On the other hand, if it is determined that there is a specific usage method in which the user's preference level is above a predetermined preference level, the setting unit 21 sets a specific usage method. The predetermined preference level can be set to an appropriate level within a range that suppresses the presentation of specific usage methods that the user does not accept.

[0055] [Processing in the information presentation system] Referring to Figure 2, the procedure for information processing by the vehicle control device 11 and the server 20 will be explained. Figure 2 is a flowchart showing an example of a basic processing procedure performed in the information presentation system 1. The processing shown in Figure 2 is executed at predetermined time intervals (for example, every 0.1 to 1 millisecond) by the processors (CPUs) of the vehicle control device 11 and the server 20, respectively.

[0056] First, in step S1, the vehicle control device 11 obtains a detection result from the detection device 12, and in the following step S2, it transmits the obtained detection result to the server 20 as usage history information. In step S3, the server 20 estimates the deterioration state based on the usage history information obtained from the vehicle 10 and / or the database 24, and in the following step S4, it understands the user's usage habits of the vehicle 10 from the usage history information.

[0057] In step S5, the server 20 identifies usage habits from the user's vehicle 10 usage habits that affect the deterioration state, and in the following step S6, it generates or selects a specific usage method for the vehicle 10 that is suitable for the user's vehicle 10 usage habits. In step S7, the server 20 transmits information about the generated or selected specific usage method to the vehicle 10. Then, in step S8, the vehicle control device 11 presents the information about the specific usage method received from the server 20 to the user using the display device 13.

[0058] Next, with reference to Figures 3-6, the procedure for how the server 20 processes information will be explained. The processes shown in Figures 3-6 are executed by the processor (CPU) of the server 20 at predetermined time intervals (for example, every 0.1 to 1 millisecond).

[0059] Figure 3 is a flowchart showing an example of the processing procedure performed when selecting a specific usage method to be presented to the user in the information presentation system 1.

[0060] First, in step S11, the server 20 obtains usage history information from at least one of the vehicle 10 and the database 24. In the following step S12, it determines whether the amount of usage history information obtained exceeds a predetermined amount. If it is determined that the amount of usage history information is less than the predetermined amount, the server 20 terminates the process. On the other hand, if it is determined that the amount of usage history information exceeds the predetermined amount, the process proceeds to step S13. The predetermined amount can be set to an appropriate amount within a range that allows for accurate estimation of the battery's degradation state or remaining lifespan from the usage history information.

[0061] In step S13, the server 20 calculates statistical values ​​such as feature quantities from the usage history information, and in the following step S14, it estimates the battery's degradation state or remaining lifespan from the usage history information. In step S15, the server 20 estimates the battery degradation factors from the statistical values ​​calculated in step S13, and in the following step S16, it retrieves candidate specific usage methods to present to the user from the database 24.

[0062] In step S17, the server 20 determines whether or not a user evaluation has been estimated for the acquired candidates. If it is determined that a user evaluation has been estimated for the acquired candidates, the process proceeds to step S18, where the server 20 selects a usage method with a relatively high evaluation among the candidates as the specified usage method. On the other hand, if it is determined that a user evaluation has not been estimated for the acquired candidates, the process proceeds to step S19, where the server 20 selects a usage method with a relatively high battery degradation suppression effect among the candidates as the specified usage method.

[0063] Next, Figure 4 is a flowchart showing an example of the processing procedure performed in the information presentation system 1 when estimating the user's evaluation of a specific usage method presented to the user.

[0064] First, in step S21, the server 20 obtains information about the specific usage method that was presented to the user immediately before, and in the following step S22, generates a feature vector corresponding to the presented specific usage method. In step S23, the server 20 generates a feature vector from the usage history information, and in the following step S24, calculates the similarity between the two calculated feature vectors.

[0065] In step S26, the server 20 determines whether the calculated similarity is equal to or greater than a predetermined similarity. If it is determined that the similarity is equal to or greater than the predetermined similarity, the process proceeds to step S27, where the server 20 determines that the user's evaluation of the specific usage method presented to the user is high. Conversely, if it is determined that the similarity is less than the predetermined similarity, the process proceeds to step S28, where the server 20 determines that the user's evaluation of the specific usage method presented to the user is low. Then, in step S29, the server 20 updates the user's evaluation of the presented specific usage method.

[0066] Next, Figure 5 is a flowchart showing an example of the processing procedure performed in the information presentation system 1 when estimating the user's preference for a specific usage method presented to the user.

[0067] First, in step S31, the server 20 obtains usage history information from at least one of the vehicle 10 and the database 24, and in the following step S32, it determines whether or not it had presented a specific usage method to the user immediately prior to the process. If it is determined that it had not presented a specific usage method to the user immediately prior to the process, the server 20 terminates the process. On the other hand, if it is determined that it had presented a specific usage method to the user immediately prior to the process, the process proceeds to step S33.

[0068] In step S33, the server 20 obtains information about the specific usage method that was presented to the user immediately before, and in the following step S34, it obtains the user's evaluation of the specific usage method presented to the user. In step S35, the server 20 trains a second trained model of user preference based on the user's evaluation of the specific usage method, and in the following step S36, it updates the user's preference for the specific usage method presented to the user.

[0069] Next, Figure 6 is a flowchart showing an example of the processing procedure performed when updating the priority for presenting specific usage methods to the user in the information presentation system 1.

[0070] First, in step S41, the server 20 retrieves candidate specific usage methods to present to the user from the database 24, and in the following step S42, it retrieves a second trained model of preference. In step S43, the server 20 uses the second trained model to calculate the user's preference for the candidate specific usage methods to present to the user, and in the following step S44, it determines whether or not there are candidates with a preference level of or higher than a predetermined level.

[0071] If it is determined that there are candidates with a preference level of or higher than a predetermined level, the process proceeds to step S45, where the server 20 updates its priority to present the candidate with the highest preference level to the user. Conversely, if it is determined that there are no candidates with a preference level of or higher than a predetermined level, the process proceeds to step S46, where the server 20 updates its priority so that no candidates are presented to the user. Then, in step S47, the server 20 saves the updated priority to the database 24.

[0072] [Embodiments of the present invention] According to this embodiment, when presenting a user of vehicle 10 with a method of using vehicle 10 that suppresses battery degradation, an information presentation method is provided that generates or selects a method of use that is suitable for the user's vehicle 10 usage habits, based on usage history information relating to the user's history of using vehicle 10, and an information presentation system 1 is provided that executes the information presentation method. This prevents presenting the user with a method of use that the user cannot perform when the goal is to suppress battery degradation of vehicle 10 by prompting the user to change how they use vehicle 10.

[0073] In the information presentation method and information presentation system 1 of this embodiment, a vehicle control device 11 mounted on the vehicle 10 and a server 20 installed outside the vehicle 10 and connected to the vehicle 10 in a communicative manner are provided, and the usage history information is acquired from at least one of the vehicle control device 11 and the server 20. This ensures that the usage history information is reliably acquired.

[0074] In the information presentation method and information presentation system 1 of this embodiment, the degradation state of the battery is estimated from the usage history information, and the usage method to be presented to the user is generated or selected based on the usage history information and the degradation state. This makes it possible to present a usage method that contributes to suppressing battery degradation.

[0075] In the information presentation method and information presentation system 1 of this embodiment, when the user is presented with the usage method, the user's evaluation of the usage method is estimated based on the information related to the usage method and the usage history information acquired after the usage method was presented. This makes it possible to accurately estimate the user's evaluation.

[0076] In the information presentation method and information presentation system 1 of this embodiment, a preference level indicating the degree to which each user likes the usage method is estimated based on the evaluation. This allows the user's preference level to be reflected in the specific usage method presented.

[0077] In the information presentation method and information presentation system 1 of this embodiment, the priority for presenting the usage methods to the user is set or updated based on the preference level. This makes it possible to present specific usage methods in an order that corresponds to the user's preference level.

[0078] The information presentation method and information presentation system 1 of this embodiment include at least one of the following: information relating to the driving history of the vehicle 10, information relating to the charging history of the battery, and information relating to the history of power supplied from the battery to an external load of the vehicle. This ensures that information necessary for suppressing battery degradation can be reliably obtained.

[0079] The information presentation method and information presentation system 1 of this embodiment include a usage method that improves at least one of the battery degradation rate and the battery remaining lifespan. This ensures that battery degradation is reliably suppressed.

[0080] In the information presentation method and information presentation system 1 of this embodiment, the degradation state of the battery at at least two different points in time is estimated from the usage history information, the degradation rate of the battery is calculated from the estimated degradation state, and the usage method to be presented to the user is generated or selected based on at least one of the degradation rate and the usage history information. This ensures that battery degradation is suppressed.

[0081] In the information presentation method and information presentation system 1 of this embodiment, the degradation state is estimated using at least one of a physical model that estimates the degradation state from information about the battery state and a trained model that has been trained to estimate the degradation state from the usage history information. This makes it possible to estimate the degradation state more accurately.

[0082] In the information presentation method and information presentation system 1 of this embodiment, the method of use is selected from a plurality of pre-set methods based on the usage history information, according to the user's usage habits. This makes it possible to present a more appropriate specific method of use to the user.

[0083] In the information presentation method and information presentation system 1 of this embodiment, a first statistical value indicating the characteristics of the usage history information is calculated from the usage history information after the usage method is presented to the user, a second statistical value indicating the characteristics of the usage history information is calculated from the usage history information when the vehicle is used in accordance with the usage method presented to the user, and the similarity between the first statistical value and the second statistical value is calculated. This makes it possible to estimate the user's evaluation of a specific usage method.

[0084] In the information presentation method and information presentation system 1 of this embodiment, the first statistical value and the second statistical value are calculated in an encoded vector format. This simplifies the estimation process in the information presentation system 1.

[0085] In the information presentation method and information presentation system 1 of this embodiment, the user's evaluation of the usage method is calculated based on the similarity. This makes it possible to obtain a more accurate user evaluation.

[0086] In the information presentation method and information presentation system 1 of this embodiment, the preference for each of the multiple usage methods is calculated in an encoded vector format. This allows the preference to be expressed quantitatively.

[0087] In the information presentation method and information presentation system 1 of this embodiment, the preference for a plurality of usage methods is estimated from the user's evaluation using at least one of a pre-set rule and a trained model that has been machine-learned to output the preference for the usage method when the user's evaluation is input, and the user and the preference are associated and stored for each user. This makes it possible to estimate the preference for each user.

[0088] In the information presentation method and information presentation system 1 of this embodiment, when the user's evaluation is calculated, the user's preference is updated based on the user's evaluation calculated immediately before and the evaluation calculated before the immediately before calculation. This enables processing using the latest preference.

[0089] In the information presentation method and information presentation system 1 of this embodiment, it is determined whether or not there is a usage method for which the user's preference level is equal to or greater than a predetermined preference level. If it is determined that there is no usage method for which the user's preference level is equal to or greater than the predetermined preference level, the usage method is not presented to the user. This makes it possible to suppress the presentation of specific usage methods that the user does not accept. [Explanation of Symbols]

[0090] 1… Information presentation system 10... Vehicles 11... Vehicle control system 12...Detection device 13…Display device 20... Server 21...Settings section 22…Evaluation and Estimation Department 23…Preference estimation part 24…Database

Claims

1. In an information presentation method implemented by an information presentation system, The information presentation system, when presenting a vehicle user with a method for using the vehicle to suppress battery degradation, generates or selects a method of use that is suitable for the user's vehicle usage habits based on usage history information relating to the user's history of using the vehicle.

2. The aforementioned information presentation system is The vehicle comprises a vehicle control device mounted on the vehicle and a server installed outside the vehicle and connected to the vehicle in a manner that enables communication with the vehicle. The information presentation method according to claim 1, wherein the usage history information is obtained from at least one of the vehicle control device and the server.

3. The aforementioned information presentation system is The degradation state of the battery is estimated from the usage history information. The information presentation method according to claim 1 or 2, which generates or selects the usage method to be presented to the user based on the usage history information and the deterioration state.

4. The information presentation method according to claim 1 or 2, wherein, when the information presentation system presents the method of use to the user, it estimates the user's evaluation of the method of use based on information related to the method of use and the usage history information acquired after the method of use has been presented.

5. The information presentation method according to claim 4, wherein the information presentation system estimates a preference level for each user based on the evaluation, indicating the degree to which the user prefers the method of use.

6. The information presentation method according to claim 5, wherein the information presentation system sets or updates the priority for presenting the usage method to the user based on the preference.

7. The information presentation method according to claim 1 or 2, wherein the usage history information includes at least one of the following: information relating to the vehicle's driving history, information relating to the battery's charging history, and information relating to the history of supplying power from the battery to an external load of the vehicle.

8. The information presentation method according to claim 1 or 2, wherein the method of use includes a method of use that improves at least one of the battery degradation rate and the remaining lifespan of the battery.

9. The aforementioned information presentation system is From the usage history information, the degradation state of the battery at at least two different points in time is estimated. From the estimated degradation state, the degradation rate of the battery is calculated. The information presentation method according to claim 1 or 2, which generates or selects the usage method to be presented to the user based on at least one of the degradation rate and the usage history information.

10. The information presentation system estimates the degradation state using at least one of a physical model that estimates the degradation state from information about the state of the battery and a trained model that has been trained to estimate the degradation state from the usage history information, according to claim 9.

11. The information presentation system, based on the usage history information, selects a usage method from a plurality of pre-set usage methods according to the usage habit, as described in claim 1 or 2.

12. The aforementioned information presentation system is After presenting the user with the usage method, a first statistical value representing the characteristics of the usage history information is calculated from the usage history information. When the vehicle is used in accordance with the usage method presented to the user, a second statistical value is calculated from the usage history information, which represents the characteristics of the usage history information. The information presentation method according to claim 1 or 2, comprising calculating the similarity between the first statistical value and the second statistical value.

13. The information presentation method according to claim 12, wherein the information presentation system calculates the first statistical value and the second statistical value in a vector format that has been encoded.

14. The information presentation method according to claim 12, wherein the information presentation system calculates the user's evaluation of the usage method based on the similarity.

15. The information presentation method according to claim 5, wherein the information presentation system calculates the preference for a plurality of usage methods in an encoded vector format.

16. The aforementioned information presentation system is Using at least one of a set rule and a trained model that has been machine-learned to output the preference for the usage method when the user's evaluation is input, the preference for a plurality of usage methods is estimated from the user's evaluation. The information presentation method according to claim 5, wherein for each user, the user and the preference level are associated and stored.

17. The information presentation method according to claim 16, wherein, when the user's evaluation is calculated, the information presentation system updates the user's preference based on the user's evaluation calculated immediately before and the evaluation calculated before the immediately before calculation.

18. The aforementioned information presentation system is Determine whether or not there exists a usage method in which the user's preference level is equal to or greater than a predetermined preference level. The information presentation method according to claim 5, wherein if it is determined that there is no usage method in which the preference level is equal to or greater than the predetermined preference level, the method of use is not presented to the user.

19. An information presentation system comprising a setting unit that, when presenting a vehicle user with a method of using the vehicle to suppress battery degradation, generates or selects a method of use that is suitable for the user's vehicle usage habits, based on usage history information relating to the user's history of using the vehicle.

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